Dissecting of the FHB resistance QTL on the short arm of wheat chromosome 2D using a comparative genomic approach: from QTL to candidate gene

Colinearity in gene content and order between rice and closely related cereal crops has been a powerful tool for gene identification. Using a comparative genomic approach, we have identified the rice genomic region syntenous to the region of the short arm of wheat chromosome 2D, on which quantitative trait loci (QTLs) for Fusarium head blight (FHB) resistance and for controlling accumulation of the mycotoxin deoxynivalenol (DON) are closely located. Utilizing markers known to reside near the FHB resistance QTL and data from several wheat genetic maps, we have limited the syntenous region to 6.8 Mb of the short arm of rice chromosome 4. From the 6.8-Mb sequence of rice chromosome 4, we found three putative rice genes that could have a role in detoxification of mycotoxins. DNA sequences of these putative rice genes were used in BLAST searches to identify wheat expressed sequence tags (ESTs) exhibiting significant similarity. Combined data from expression analysis and gene mapping of wheat homologues and results of analysis of DON accumulation using doubled haploid populations revealed that a putative gene for multidrug resistance-associated protein (MRP) is a possible candidate for the FHB resistance and/or DON accumulation controlling QTLs on wheat chromosome 2DS and can be used as a molecular marker to eliminate the susceptible allele when the Chinese wheat variety Sumai 3 is used as a resistance source. Electronic supplementary material  The online version of this article (doi:) contains supplementary material, which is available to authorized users.     

High-resolution mapping of <Emphasis Type="Italic">Rsn1</Emphasis>, a locus controlling sensitivity of rice to a necrosis-inducing phytotoxin from <Emphasis Type="Italic">Rhizoctonia solani</Emphasis> AG1-IA

Rhizoctonia solani is a necrotrophic fungal pathogen that causes disease on many crop-plant species. Anastomosis group 1-IA is the causal agent of sheath blight of rice (Oryza sativa L.), one of the most important rice diseases worldwide. R. solani AG1-IA produces a necrosis-inducing phytotoxin and rice cultivar’s sensitivity to the toxin correlates with disease susceptibility. Unlike genetic analyses of sheath blight resistance where resistance loci have been reported as quantitative trait loci, phytotoxin sensitivity is inherited as a Mendelian trait that permits high-resolution mapping of the sensitivity genes. An F₂ mapping population derived from parent cultivars ‘Cypress’ (toxin sensitive) and ‘Jasmine 85’ (toxin insensitive) was used to map Rsn1, the necrosis-inducing locus. Initial mapping based on 176 F₂ progeny and 69 simple sequence repeat (SSR) markers located Rsn1 on the long arm of chromosome 7, with tight linkage to SSR marker RM418. A high-resolution genetic map of the region was subsequently developed using a total of 1,043 F₂ progeny, and Rsn1 was mapped to a 0.7 cM interval flanked by markers NM590 and RM418. Analysis of the corresponding 29 Kb genomic sequences from reference cultivars ‘Nipponbare’ and ‘93-11’ revealed the presence of four putative genes within the interval. Two are expressed cytokinin-O-glucosyltransferases, which fit an apoptotic pathway model of toxin activity, and are individually being investigated further as potential candidates for Rsn1.     

Fine Mapping QTL for Drought Resistance Traits in Rice (<Emphasis Type="Italic">Oryza sativa</Emphasis> L.) Using Bulk Segregant Analysis

Drought stress is a major limitation to rice (Oryza sativa L.) yields and its stability, especially in rainfed conditions. Developing rice cultivars with inherent capacity to withstand drought stress would improve rainfed rice production. Mapping quantitative trait loci (QTLs) linked to drought resistance traits will help to develop rice cultivars suitable for water-limited environments through molecular marker-assisted selection (MAS) strategy. However, QTL mapping is usually carried out by genotyping large number of progenies, which is labour-intensive, time-consuming and cost-ineffective. Bulk segregant analysis (BSA) serves as an affordable strategy for mapping large effect QTLs by genotyping only the extreme phenotypes instead of the entire mapping population. We have previously mapped a QTL linked to leaf rolling and leaf drying in recombinant inbred (RI) lines derived from two locally adapted indica rice ecotypes viz., IR20/Nootripathu using BSA. Fine mapping the QTL will facilitate its application in MAS. BSA was done by bulking DNA of 10 drought-resistant and 12 drought-sensitive RI lines. Out of 343 rice microsatellites markers genotyped, RM8085 co-segregated among the RI lines constituting the respective bulks. RM8085 was mapped in the middle of the QTL region on chromosome 1 previously identified in these RI lines thus reducing the QTL interval from 7.9 to 3.8 cM. Further, the study showed that the region, RM212–RM302–RM8085–RM3825 on chromosome 1, harbours large effect QTLs for drought-resistance traits across several genetic backgrounds in rice. Thus, the QTL may be useful for drought resistance improvement in rice through MAS and map-based cloning.     

Fine mapping of three quantitative trait loci for late blight resistance in tomato using near isogenic lines (NILs) and sub-NILs

An earlier study identified quantitative trait loci (QTLs) lb4, lb5b, and lb11b for quantitative resistance to Phytophthora infestans (late blight) in a backcross population derived from crossing susceptible cultivated tomato (Lycopersicon esculentum) with resistant L. hirsutum. The QTLs were located in intervals spanning 28–47 cM. Subsequently, near-isogenic lines (NILs) were developed for lb4, lb5b, and lb11b by marker-assisted backcrossing to L. esculentum. Sub-NILs containing overlapping L. hirsutum segments across each QTL region were selected and used to validate the QTL effects, fine-map QTLs, and evaluate potential linkage drag between resistance QTLs and QTLs for horticultural traits. The NILs and sub-NILs were evaluated for disease resistance and eight horticultural traits at three field locations. Resistance QTLs were detected in all three sets of NIL lines, confirming the BC₁ mapping results. Lb4 mapped near TG609, and between TG182 and CT194, on chromosome 4, a 6.9-cM interval; lb5b mapped to an 8.8-cM interval between TG69a and TG413 on chromosome 5, with the most likely position near TG23; and lb11b mapped to a 15.1-cM interval on chromosome 11 between TG194 and TG400, with the peak centered between CT182 and TG147. Most QTLs for horticultural traits were identified in intervals adjacent to those containing the late blight resistance QTLs. Fine mapping of these QTLs permits the use of marker-assisted selection for the precise introgression of L. hirsutum segments containing late blight resistance alleles separately from those containing deleterious alleles at horticulturally important QTLs.Electronic Supplementary Material Supplementary material is available in the online version of this article at Communicated by D.B. Neale     

Mapping quantitative trait loci controlling sheath blight resistance in two rice cultivars (Oryza sativa L.)

Rice sheath blight, caused by Rhizoctonia solani Kühn, is one of the three major diseases of rice. The present study was conducted with an F₂ clonal population of Jasmine 85/Lemont. The F₂ population, including 128 clonal families, was inoculated by short toothpicks incubated with a strain, RH-9 of the fungus. Based on field disease evaluations in 2 years and a genetic map with 118 evenly distributed molecular markers, we identified six quantitative trait loci (QTLs) contributing to sheath blight resistance. These QTLs, qSB-2, qSB-3, qSB-7, qSB-9-1, qSB-9-2 and qSB-11, were located on chromosomes 2, 3, 7, 9 and 11, respectively. The respective alleles of qSB-2, qSB-3, qSB-7, and qSB-9-2 from Jasmine 85 could explain 21.2%, 26.5%, 22.2% and 10.1% of the total phenotypic variation, respectively; while the alleles of qSB-9-1 and qSB-11 from Lemont could explain 9.8% and 31.2% of the total phenotypic variation. Of these qSB-2 and qSB-11 could be detected in both years, while remaining loci were detected only in a single year. Furthermore, four QTLs (qHD-2, qHD-3, qHD-5 and qHD-7) controlling heading date and three QTLs (qPH-3, qPH-4 and qPH-11) controlling plant height were also identified. Though rice sheath blight resistance may be influenced by morphological traits, such as heading date and plant height, in the present study most detected resistance loci were not linked to the loci for heading date or plant height. Received: 1 September 1999 / Accepted: 24 January 2000     

Identification of Quantitative Trait Loci for Bacterial Blight Resistance Derived from Oryza meyeriana and Agronomic Traits in Recombinant Inbred Lines of Oryza sativa

Bacterial blight (BB) is one of the major diseases that affect rice productivity. In previous studies, BB resistance was transferred to cultivated rice Oryza sativa from wild rice Oryza meyeriana using asymmetric somatic hybridization. One of the resistant hybrid progenies (Y73) has also been shown to possess novel resistance gene(s) different from any of those previously associated with BB resistance. We have mapped quantitative trait loci (QTLs) for BB resistance in a recombinant inbred line (RIL) population derived from a cross between Y73 and a BB‐susceptible cv. IR24. Five QTLs were detected where Y73 alleles contributed to increased BB resistance. Three minor QTLs were identified on chromosomes 3, 10 and 11, and two major QTLs on chromosomes 1 and 5, respectively. QTL on chromosome 5, designated qBBR5, had the strongest effect on BB resistance, explaining approximately 37% of the phenotypic variance. Using the same RIL population, we also mapped QTLs for agronomic traits including plant height (PH), heading date (HD), plant yield (PYD) and PYD component traits. A total of 21 QTLs were identified, of which four were detected for PH, six for HD, three for panicle number per plant (PNPP), one for spikelets per panicle (SPP), six for 1000‐grain weight (TGW) and one for PYD. qPH1 (a QTL for PH) was found in the same interval as qBBR1 for BB resistance, and qHD11 for HD and qBBR11 for BB resistance also shared a similar interval. Additionally, BB resistance was significantly correlated with PH or HD in the RIL population. This suggests that the resistance genes may have pleiotropic effects on, or close linkage to, genes controlling PH or HD. These results will help deduce the resistance mechanisms of the novel resistance gene(s) and provide the basis for cloning them and using them in marker‐assisted breeding.     

Phenotyping of Partial Physiological Resistance to Rice Sheath Blight

Sheath blight, caused by Rhizoctonia solani, is one of the most important rice diseases worldwide especially under irrigated agro‐ecosystems. To date, no rice accession with complete resistance to sheath blight has been reported. However, a number of genotypes with varying levels of resistance have been reported. Twelve genotypes (including mega varieties) viz. Tetep, Jasmine 85, Te‐Qing, Duduruchi, Betichikon, Khatochalani, D‐6766, D‐256, Swarna, Sarju‐52, MTU‐1010 and Samba Mashuri were evaluated for quantitative measurement of partial physiological resistance to sheath blight under controlled conditions using detached tiller method. Three independent experiments, each involving three replications, were conducted. Seven days after inoculation, the following disease variables were measured: number of lesions, lesion length, vertical sheath colonization (VSC) on the tiller, disease severity, relative vertical sheath colonization (RVSC) and survival of the leaf blade. Variation between rice genotypes was observed for all the disease variables. Disease severity and VSC were the two most correlated variables, whereas the number of lesions and mean lesion length were the least correlated variables. The ranking of varieties often differed depending on the disease variable considered. Amongst the genotypes tested, D‐256, Tetep and Jasmin‐85 had the lowest number of lesions and disease severity. Similarly, Tetep and D‐256 showed the lowest levels of RVSC, whilst Jasmine‐85 was found to be intermediate. D‐6766, Samba Mashuri and Betichikon showed the highest levels of disease variables. The fraction of dead leaves ranged from 0.00 to 0.38. No dead leaves were observed in Te‐Qing, Swarna and MTU‐1010. The highest fraction of dead leaves was observed for Betichikon (0.38) followed by Duduruchi and D‐6766 (0.33). Our results suggest that this method in combination with other phenotyping methods could be used to quantify partial resistance to rice sheath blight.     

QTL analysis for ascochyta blight resistance in an intraspecific population of chickpea (<Emphasis Type="Italic">Cicer arietinum</Emphasis> L.)

In both controlled environment and the field, six QTLs for ascochyta blight resistance were identified in three regions of the genome of an intraspecific population of chickpea using the IDS and AUDPC disease scoring systems. One QTL-region was detected from both environments, whereas the other two regions were detected from each environment. All the QTL-regions were significantly associated with ascochyta blight resistance using either of the disease scoring systems. The QTLs were verified by multiple interval mapping, and a two-QTL genetic model with considerable epistasis was established for both environments. The major QTLs generally showed additive gene action, as well as dominance inter-locus interaction in the multiple genetic model. All the QTLs were mapped near a RGA marker. The major QTLs were located on LG III, which was mapped with five different types of RGA markers. A CLRR-RGA marker and a STMS marker flanked QTL 6 for controlled environment resistance at 0.06 and 0.04 cM, respectively. Other STMS markers flanked QTL 1 for field resistance at a 5.6 cM interval. After validation, these flanking markers may be used in marker-assisted selection to breed for elite chickpea cultivars with durable resistance to ascochyta blight. The tight linkage of RGA markers to the major QTL on LG III will allow map-based cloning of the underlying resistance genes.Communicated by P. Langridge     

Meta-analysis of Yield QTLs Derived from Inter-specific Crosses of Rice Reveals Consensus Regions and Candidate Genes

Several reports on mapping and introgression of quantitative trait loci (QTLs) for yield and related traits from wild species showed their importance in yield improvement. The aim of this study was to locate common major effect, consistent and precise yield QTLs across the wild species of rice by applying genome-wide QTL meta-analysis for their use in marker-aided selection (MAS) and candidate gene identification. Seventy-six yield QTLs reported in 11 studies involving inter-specific crosses were projected on a consensus map consisting of 699 markers. The integration of 11 maps resulted in a consensuses map of 1,676 cM. The number of markers ranged from 32 on chromosome 12 to 96 on chromosome 1. The order of markers between consensus map and original map was generally consistent. Meta-analysis of 68 yield QTLs resulted in 23 independent meta-QTLs on ten different chromosomes. Eight meta-QTLs were less than 1.3 Mb. The smallest confidence interval of a meta-QTL (MQTL) was 179.6 kb. Four MQTLs were around 500 kb and two of these correspond to a reasonably small genetic distance 4.6 and 5.2 cM, respectively, and suitable for MAS. MQTL8.2 was 326-kb long with a 35-cM interval indicating it was in a recombination hot spot and suitable for fine mapping. Our results demonstrate the narrowing down of initial yield QTLs by Meta-analysis and thus enabling short listing of QTLs worthy of MAS or fine mapping. The candidate genes shortlisted are useful in validating their function either by loss of function or over expression.     

QTL Mapping of Downy Mildew Resistance in an Introgression Line Derived from Interspecific Hybridization Between Cucumber and Cucumis hystrix

Downy mildew (DM), caused by Pseudoperonospora cubensis (Berk. & M.A. Curtis) Rostovzev, is a worldwide major disease of cucumbers (Cucumis sativus L.). By screening 10 introgression lines (ILs) derived from interspecific hybridization between cucumber and the wild Cucumis, C. hystrix, through a whole plant assay, one introgression line (IL52) was identified with high DM‐resistance. IL52 was further used as a resistant parent to make an F₂ population with ‘changchunmici’ (susceptible parent). The F₂ population (300 plants) was investigated for DM‐yellowing, DM‐necrosis and DM‐resistance in the adult stage. A genetic map spanning 642.5 cM with 104 markers was constructed and used for QTL analysis from the population. Three QTL regions were identified on chromosome 5 and chromosome 6. By interval mapping analysis, two QTLs for DM‐resistance were determined on chromosome 5 (DM_5.1 and DM_5.2), which explained 17.9% and 14.2% of the variation, respectively. QTLs for DM‐yellowing were in the same regions as DM‐resistance. For DM‐necrosis, by interval mapping analysis, one QTL was determined on chromosome 5 (Necr_5.1) that explained 18.3% of the variation and one on chromosome 6 (Necr_6.1) that explained 13.9% of the variation. Our results indicated that the identification of molecular markers linked to the QTLs could be further applied for marker‐assisted selection (MAS) of downy mildew resistance in cucumber.     

QTL sequencing strategy to map genomic regions associated with resistance to ascochyta blight in chickpea

Whole‐genome sequencing‐based bulked segregant analysis (BSA) for mapping quantitative trait loci (QTL) provides an efficient alternative approach to conventional QTL analysis as it significantly reduces the scale and cost of analysis with comparable power to QTL detection using full mapping population. We tested the application of next‐generation sequencing (NGS)‐based BSA approach for mapping QTLs for ascochyta blight resistance in chickpea using two recombinant inbred line populations CPR‐01 and CPR‐02. Eleven QTLs in CPR‐01 and six QTLs in CPR‐02 populations were mapped on chromosomes Ca1, Ca2, Ca4, Ca6 and Ca7. The QTLs identified in CPR‐01 using conventional biparental mapping approach were used to compare the efficiency of NGS‐based BSA in detecting QTLs for ascochyta blight resistance. The QTLs on chromosomes Ca1, Ca4, Ca6 and Ca7 overlapped with the QTLs previously detected in CPR‐01 using conventional QTL mapping method. The QTLs on chromosome Ca4 were detected in both populations and overlapped with the previously reported QTLs indicating conserved region for ascochyta blight resistance across different chickpea genotypes. Six candidate genes in the QTL regions identified using NGS‐based BSA on chromosomes Ca2 and Ca4 were validated for their association with ascochyta blight resistance in the CPR‐02 population. This study demonstrated the efficiency of NGS‐based BSA as a rapid and cost‐effective method to identify QTLs associated with ascochyta blight in chickpea.     

Genetic Structure and Aggressiveness of Rhizoctonia solani AG1‐IA,the Cause of Sheath Blight of Rice in Southern China

One hundred and eighty isolates of Rhizoctonia solani AG1‐IA, the causal agent of rice sheath blight, were obtained from six locations in southern China. The genetic structure of R. solani isolates was investigated using random amplified polymorphic DNA (RAPD) markers, and a considerable genetic variation among R. solani isolates was observed. Most of the genetic diversity was distributed within populations, rather than among them. The distribution pattern of the genetic variation of R. solani appears to be the result of high gene flow (Nm) and low‐genetic differentiation among populations. The aggressiveness of R. solani was visually assessed by rice seedlings of five different cultivars in the glasshouse. All isolates tested were found to induce significantly different levels of disease severity, reflecting considerable variation in aggressiveness. The isolates were divided into highly virulent, moderately virulent and weakly virulent groups, and the moderately virulent isolates were dominant in R. solani population. No significant correlation was observed among the genetic similarity, pathogenic aggressiveness and geographical origins of the isolates. Information obtained from this study may be useful for breeding for improved resistance to sheath blight.     

Exploring the quantitative resistance to <Emphasis Type="Italic">Pseudomonas syringae</Emphasis> pv. <Emphasis Type="Italic">phaseolicola</Emphasis> in common bean (<Emphasis Type="Italic">Phaseolus vulgaris</Emphasis> L.)

Pseudomonas syringae pv. phaseolicola is an important disease that causes halo blight in common bean. The genetic mechanisms underlying quantitative halo blight resistance are poorly understood in this species, as most disease studies have focused on qualitative resistance. The present work examines the genetic basis of quantitative resistance to the nine halo blight races in different organs (primary and trifoliate leaf, stem and pod) of an Andean recombinant inbred line (RIL) progeny. Using a multi-environment quantitative trait locus (QTL) mapping approach, 76 and 101 main-effect and epistatic QTLs were identified, respectively. Most of the epistatic interactions detected were due to loci without detectable QTL additive main effects. Main and epistatic QTLs detected were mainly consistent across the environment conditions. The homologous genomic regions corresponding to 26 of the 76 main-effect detected QTLs were positive for the presence of resistance-associated gene cluster encoding nucleotide-binding and leucine-rich repeat (NL) proteins and known defence genes. Main-effect QTLs for resistance to races 3, 4 and 5 in leaf, stem and pod were located on chromosome 2 within a 3.01-Mb region, where a cluster of nine NL genes was detected. The NL gene Phvul.002G323300 is located in this region, which can be considered an important putative candidate gene for the non-organ-specific QTL identified here. The present research provides essential information not only for the better understanding of the plant-pathogen interaction but also for the application of genomic assisted breeding for halo blight resistance in common bean.     

Targeted discovery of quantitative trait loci for resistance to northern leaf blight and other diseases of maize

To capture diverse alleles at a set of loci associated with disease resistance in maize, heterogeneous inbred family (HIF) analysis was applied for targeted QTL mapping and near-isogenic line (NIL) development. Tropical maize lines CML52 and DK888 were chosen as donors of alleles based on their known resistance to multiple diseases. Chromosomal regions (“bins”; n = 39) associated with multiple disease resistance (MDR) were targeted based on a consensus map of disease QTLs in maize. We generated HIFs segregating for the targeted loci but isogenic at ~97% of the genome. To test the hypothesis that CML52 and DK888 alleles at MDR hotspots condition broad-spectrum resistance, HIFs and derived NILs were tested for resistance to northern leaf blight (NLB), southern leaf blight (SLB), gray leaf spot (GLS), anthracnose leaf blight (ALB), anthracnose stalk rot (ASR), common rust, common smut, and Stewart’s wilt. Four NLB QTLs, two ASR QTLs, and one Stewart’s wilt QTL were identified. In parallel, a population of 196 recombinant inbred lines (RILs) derived from B73 × CML52 was evaluated for resistance to NLB, GLS, SLB, and ASR. The QTLs mapped (four for NLB, five for SLB, two for GLS, and two for ASR) mostly corresponded to those found using the NILs. Combining HIF- and RIL-based analyses, we discovered two disease QTLs at which CML52 alleles were favorable for more than one disease. A QTL in bin 1.06–1.07 conferred resistance to NLB and Stewart’s wilt, and a QTL in 6.05 conferred resistance to NLB and ASR.     

Molecular mapping for fruit-related traits,and joint identification of candidate genes and selective sweeps for seed size in melon

Melon is a popular fruit vegetable crop worldwide with diverse morphological variation. We report a high-density genetic map of melon and nine major QTLs with physical region ranging from 43.47 kb to 1.89 Mb. Importantly, two seed-related trait QTLs were repeatedly detected in two environments, and the mapping region was narrowed to 522 kb according to a regional linkage analysis. A total of 40 annotated genes were screened for nonsynonymous variations, of which EVM0009818, involved in cytokinin-activated signaling, was differentially expressed in the young fruits of parents based on RNA-seq. Selective sweep analysis identified 152 sweep signals for seed size, including the two seed-related QTLs and nine homologs that have been verified to regulate seed size in Arabidopsis or rice. This work illustrates the power of a joint analysis combining resequencing-based genetic map for QTL mapping and a combination of KASP genotyping and RNA-seq analysis to facilitate QTL fine mapping.     

Major-effect QTLs for stem and foliage resistance to late blight in the wild potato relatives <Emphasis Type="Italic">Solanum sparsipilum</Emphasis> and <Emphasis Type="Italic">S. spegazzinii</Emphasis> are mapped to chromosome X

To find out new resistance sources to late blight in the wild germplasm for potato breeding, we examined the polygenic resistance of Solanum sparsipilum and S. spegazzinii by a quantitative trait locus (QTL) analysis. We performed stem and foliage tests under controlled conditions in two diploid mapping progenies. Four traits were selected for QTL detection. A total of 30 QTLs were mapped, with a large-effect QTL region on chromosome X detected in both potato relatives. The mapping of literature-derived markers highlighted colinearities with published late blight QTLs or R-genes. Results showed (a) the resistance potential of S. sparsipilum and S. spegazzinii for late blight control, and (b) the efficacy of the stem test as a complement to the foliage test to break down the complex late blight resistance into elementary components. The relationships of late blight resistance QTLs with R-genes and maturity QTLs are discussed.     

Mapping QTLs conferring early blight (Alternaria solani) resistance in a Lycopersicon esculentum×L. hirsutum cross by selective genotyping

Most commercial cultivars of tomato, Lycopersicon esculentum Mill., are susceptible to early blight (EB), a devastating fungal (Alternaria solani Sorauer) disease of tomato in the U.S. and elsewhere in the world. Currently, sanitation, long crop rotation, and routine application of fungicides are the most common disease control measures. Although no source of genetic resistance is known within the cultivated species of tomato, resistant resources have been identified within related wild species. The purpose of this study was to identify and validate quantitative trait loci (QTLs) conferring EB resistance in an accession (PI126445) of the tomato wild species L. hirsutum Humb. and Bonpl. by using a selective genotyping approach. A total of 820 BC₁ plants of a cross between an EB susceptible tomato breeding line (NC84173; maternal and recurrent parent) and PI126445 were grown in a greenhouse. During late seedling stage, plants were inoculated with mixed isolates of A. solani and subsequently evaluated for EB symptoms. The most resistant (75 plants = 9.1%) and most susceptible (80 = 9.8%) plants were selected and subsequently transplanted into a field where natural infestation of EB was severe. Plants were grown to maturity and evaluated for final disease severity. From among the 75 resistant plants, 46 (5.6% of the total) that exhibited the highest resistance, and from among the 80 susceptible plants, 30 (3.7% of the total) that exhibited the highest susceptibility, were selected. The 76 selected plants, representing the two extreme tails of the response distribution, were genotyped for 145 restriction fragment length polymorphism (RFLP) markers and 34 resistance gene analogs (RGAs). A genetic linkage map, spanning approximately 1298 cM of the 12 tomato chromosomes with an average marker distance of 7.3 cM, was constructed. A trait-based marker analysis (TBA), which measures differences in marker allele frequencies between extreme tails of a population, detected seven QTLs for EB resistance, one on each of chromosomes 3, 4, 5, 6, 8, 10 and 11. Of these, all but the QTL on chromosome 3 were contributed from the resistant wild parent, PI126445. The standardized effects of the QTLs ranged from 0.45 to 0.81 phenotypic standard deviations. Four of the seven QTLs were previously identified in a study where different populations and mapping strategy were used. The high level of correspondence between the two studies indicated the reliability of the detected QTLs and their potential use for marker-assisted breeding for EB resistance. The location of several RGAs coincided with locations of EB QTLs or known tomato resistance genes (R genes), suggesting that these RGAs could be associated with disease resistance. Furthermore, similar to that for many R gene families, several RGA loci were identified in clusters, suggesting their potential evolutionary relationship with R genes.     

Association between sheath blight resistance and chitinase activity in transgenic rice plants expressing McCHIT1 from bitter melon

No usable resources with high-level resistance to sheath blight (SB) have yet been found in rice germplasm resources worldwide. Therefore, creating and breeding new disease-resistant rice resources with sheath blight resistance (SBR) are imperative. In this study, we inoculated rice plants with hyphae of the highly pathogenic strain RH-9 of rice SB fungus Rhizoctonia solani to obtain eight stable transgenic rice lines harbouring the chitinase gene (McCHIT1) of bitter melon with good SBR in the T₅ generation. The mean disease index for SB of wild-type plants was 92% and 37–44% in transgenic lines. From 24 h before until 120 h after inoculation with R. solani, chitinase activity in stable transgenic plants with increased SBR was 2.0–5.5 and 1.8–2.7 times that of wild-type plants and plants of a disease-susceptible stable transgenic line, respectively. The correlation between SBR and chitinase activity in McCHIT1-transgenic rice line plants was significant. This work stresses how McCHIT1 from bitter melon can be used to protect rice plants from SB infection.

     

水稻株形对纹枯病抗性的影响

利用240份源于珍汕97B/明恢63的重组自交系水稻(Oryza sativa L.)群体,连续2年调查纹枯病病级与水稻生育期、株高和叶片长宽等18个株形性状的关系.对株形性状与纹枯病病级进行了偏相关分析.实验结果,只有植株松紧度与病级表型偏相关两年中都达到了显著或极显著水平,倒2叶基角、穗层整齐度等8个性状与病级之间的偏相关只有一年达显著或极显著水平.结合构建的分子标记遗传连锁图谱,对各性状进行QTL定位.在抗纹枯病QTL相近区间仅检测到控制分蘖角、植株松紧度和倒2叶基角的QTLS,未发现其余株形性状QTLs与抗纹枯病QTLs分布在同一染色体上.结果表明,水稻对纹枯病的抗性主要是由本身抗性基因控制,株形对纹枯病抗性表达的影响主要是间接影响,即通过改变田间小气候而影响发病程度.抗纹枯病育种在累加主效抗纹枯病QTLs的同时,也要注重选择不利于纹枯病发展的株形性状.     

Detection of a quantitative trait locus for both foliage and tuber resistance to late blight [Phytophthora infestans (Mont.) de Bary] on chromosome 4 of a dihaploid potato clone (Solanum tuberosum subsp. tuberosum)

Linkage analysis, Kruskal–Wallis analysis, interval mapping and graphical genotyping were performed on a potato diploid backcross family comprising 120 clones segregating for resistance to late blight. A hybrid between the Solanum tuberosum dihaploid clone PDH247 and the long-day-adapted S. phureja clone DB226(70) had been crossed to DB226(70) to produce the backcross family. Eighteen AFLP primer combinations provided 186 and 123 informative maternal and paternal markers respectively, with 63 markers in common to both parents. Eleven microsatellite (SSR) markers proved useful for identifying chromosomes. Linkage maps of both backcross parents were constructed. The results of a Kruskal–Wallis analysis, interval mapping and graphical genotyping were all consistent with a QTL or QTLs for blight resistance between two AFLP markers 30 cM apart on chromosome 4, which was identified by a microsatellite marker. The simplest explanation of the results is a single QTL with an allele from the dihaploid parent conferring resistance to race 1, 4 of P. infestans in the foliage in the glasshouse and to race 1, 2, 3, 4, 6, 7 in the foliage in the field and in tubers from glasshouse raised plants. The QTL was of large effect, and explained 78 and 51% of the variation in phenotypic scores for foliage blight in the glasshouse and field respectively, as well as 27% of the variation in tuber blight. Graphical genotyping and the differences in blight scores between the parental clones showed that all of the foliage blight resistance is accounted for by chromosome 4, whereas undetected QTLs for tuber resistance probably exist on other chromosomes. Graphical genotyping also explained the lack of precision in mapping the QTL(s) in terms of lack of appropriate recombinant chromosomes.